Incremental Deployment and Throughput Maximization Routing for a Hybrid SDN

被引:91
作者
Xu, Hongli [1 ,2 ]
Li, Xiang-Yang [1 ,3 ]
Huang, Liusheng [1 ,2 ]
Deng, Hou [1 ,2 ]
Huang, He [4 ]
Wang, Haibo [1 ,2 ]
机构
[1] Univ Sci & Technol China, Sch Comp Sci & Technol, Hefei 230027, Peoples R China
[2] Univ Sci & Technol China, Suzhou Inst Adv Study, Suzhou 215123, Peoples R China
[3] IIT, Dept Comp Sci, Chicago, IL 60616 USA
[4] Soochow Univ, Sch Comp Sci & Technol, Suzhou 215006, Peoples R China
关键词
Software defined networks; incremental deployment; cover; splittable flow; throughput maximization; SOFTWARE-DEFINED NETWORKING;
D O I
10.1109/TNET.2017.2657643
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
To explore the advantages of software defined network (SDN), while preserving the legacy networking systems, a natural deployment strategy is to deploy a hybrid SDN incrementally to improve the network performance. In this paper, we address two technical challenges: an incremental deployment strategy and a throughput-maximization routing, for deploying a hybrid network incrementally. For incremental deployment, we propose a heuristic algorithm for deploying a hybrid SDN under the budget constraint, and prove the approximate factor of 1 - 1/e. For throughput-maximization routing, we apply a depth-first-search method and a randomized rounding mechanism to solve the multi-commodity h-splittable flow routing problem in a hybrid SDN, where h >= 1. We also prove that our method has approximation ratio O(1/log N), where N is the number of links in a hybrid SDN. We then show, by both analysis and simulations, that our algorithms can obtain significant performance gains and perform better than the theoretical worst-case bound. For example, our incremental deployment scheme helps to enhance the throughout about 40% compared with the previous deployment scheme by deploying a small number of SDN devices, and the proposed routing algorithm can improve the throughput about 31% compared with ECMP in hybrid networks.
引用
收藏
页码:1861 / 1875
页数:15
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